Displaying publications 41 - 60 of 318 in total

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  1. Fulltext Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh
    Yaseen ZM, Ali M, Sharafati A, Al-Ansari N, Shahid S
    Sci Rep, 2021 Feb 09;11(1):3435.
    PMID: 33564055 DOI: 10.1038/s41598-021-82977-9
    A noticeable increase in drought frequency and severity has been observed across the globe due to climate change, which attracted scientists in development of drought prediction models for mitigation of impacts. Droughts are usually monitored using drought indices (DIs), most of which are probabilistic and therefore, highly stochastic and non-linear. The current research investigated the capability of different versions of relatively well-explored machine learning (ML) models including random forest (RF), minimum probability machine regression (MPMR), M5 Tree (M5tree), extreme learning machine (ELM) and online sequential-ELM (OSELM) in predicting the most widely used DI known as standardized precipitation index (SPI) at multiple month horizons (i.e., 1, 3, 6 and 12). Models were developed using monthly rainfall data for the period of 1949-2013 at four meteorological stations namely, Barisal, Bogra, Faridpur and Mymensingh, each representing a geographical region of Bangladesh which frequently experiences droughts. The model inputs were decided based on correlation statistics and the prediction capability was evaluated using several statistical metrics including mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R), Willmott's Index of agreement (WI), Nash Sutcliffe efficiency (NSE), and Legates and McCabe Index (LM). The results revealed that the proposed models are reliable and robust in predicting droughts in the region. Comparison of the models revealed ELM as the best model in forecasting droughts with minimal RMSE in the range of 0.07-0.85, 0.08-0.76, 0.062-0.80 and 0.042-0.605 for Barisal, Bogra, Faridpur and Mymensingh, respectively for all the SPI scales except one-month SPI for which the RF showed the best performance with minimal RMSE of 0.57, 0.45, 0.59 and 0.42, respectively.
  2. Fulltext Metabolite Profiling of Malaysian Gracilaria edulis Reveals Eplerenone as Novel Antibacterial Compound for Drug Repurposing Against MDR Bacteria
    Asghar A, Tan YC, Shahid M, Yow YY, Lahiri C
    Front Microbiol, 2021;12:653562.
    PMID: 34276590 DOI: 10.3389/fmicb.2021.653562
    With a continuous threat of antimicrobial resistance on human health worldwide, efforts for new alternatives are ongoing for the management of bacterial infectious diseases. Natural products of land and sea, being conceived to be having fewer side effects, pose themselves as a welcome relief. In this respect, we have taken a scaffolded approach to unearthing the almost unexplored chemical constituents of Malaysian red seaweed, Gracilaria edulis. Essentially, a preliminary evaluation of the ethyl acetate and acetone solvent extracts, among a series of six such, revealed potential antibacterial activity against six MDR species namely, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella enterica, methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pyogenes, and Bacillus subtilis. Detailed analyses of the inlying chemical constituents, through LC-MS and GC-MS chromatographic separation, revealed a library of metabolic compounds. These were led for further virtual screening against selected key role playing proteins in the virulence of the aforesaid bacteria. To this end, detailed predictive pharmacological analyses added up to reinforce Eplerenone as a natural alternative from the plethora of plausible bioactives. Our work adds the ongoing effort to re-discover and repurpose biochemical compounds to combat the antimicrobial resistance offered by the Gram-positive and the -negative bacterial species.
  3. Fulltext Anxiety, OCD, delusions, and religiosity among the general public during the COVID-19 pandemic
    Abdullah DI, Parveen DS, Shahid Khan DN, Abdullah D
    Int Soc Sci J, 2021 Jul 05.
    PMID: 34548689 DOI: 10.1111/issj.12284
    The COVID-19 outbreak has not only affected the physical health of the public but also resulted in severe psychological outcomes. This study aims to investigate the psychological effects of the COVID-19 outbreak on Pakistan's general public. In order to identify the main psychological factors that have emerged due to the current pandemic, extensive literature and opinion pieces of psychologists were reviewed. After a thorough study of the existing scholarship, four main psychological factors were investigated: stress and anxiety, obsessive compulsive disorder (OCD), delusions of getting infected from the disease, and religiosity. A research survey was circulated among the sample population online. A total 356 valid responses were received in the period of two to three weeks. Findings showed that the respondents reported a moderate level of anxiety, occasional symptoms of OCD, and delusions. However, respondents showed a high inclination toward religion during the current pandemic situation. Furthermore, respondents highlighted a few other psychological factors, such as financial strain and loneliness, in the survey. The primary sources of COVID-19-related information were social media and television among the general public of Pakistan. Finally, guidelines and tips from the reviewed psychologists and psychiatrists on overcoming the highlighted psychological problems that have arisen due to the COVID-19 outbreak were summarised.
  4. Fulltext Suppression of Cisplatin-Induced Vomiting byCannabis sativain Pigeons: Neurochemical Evidences
    Ullah I, Subhan F, Alam J, Shahid M, Ayaz M
    Front Pharmacol, 2018;9:231.
    PMID: 29615907 DOI: 10.3389/fphar.2018.00231
    Cannabis sativa
    (CS, familyCannabinaceae) has been reported for its anti-emetic activity against cancer chemotherapy-induced emesis in animal models and in clinics. The current study was designed to investigateCSfor potential effectiveness to attenuate cisplatin-induced vomiting in healthy pigeons and to study the impact on neurotransmitters involved centrally and peripherally in the act of vomiting. High-performance liquid chromatography system coupled with electrochemical detector was used for the quantification of neurotransmitters 5-hydroxytryptamine (5HT), dopamine (DA) and their metabolites; Di-hydroxy Phenyl Acetic acid (Dopac), Homovanillic acid (HVA), and 5-hydroxy indole acetic acid (5HIAA) centrally in specific brain areas (area postrema and brain stem) while, peripherally in small intestine. Cisplatin (7 mg/kg i.v.) induce emesis without lethality across the 24 h observation period.CShexane fraction (CS-HexFr; 10 mg/kg) attenuated cisplatin-induced emesis ∼ 65.85% (P< 0.05); the reference anti-emetic drug, metoclopramide (MCP; 30 mg/kg), produced ∼43.90% reduction (P< 0.05). At acute time point (3rdh), CS-HexFr decreased (P< 0.001) the concentration of 5HT and 5HIAA in the area postrema, brain stem and intestine, while at 18thh (delayed time point) CS-HexFr attenuated (P< 0.001) the upsurge of 5HT caused by cisplatin in the brain stem and intestine and dopamine in the area postrema.CS-HexFr treatment alone did not alter the basal neurotransmitters and their metabolites in the brain areas and intestine except 5HIAA and HVA, which were decreased significantly. In conclusion the anti-emetic effect ofCS-HexFr is mediated by anti-serotonergic and anti-dopaminergic components in a blended manner at the two different time points, i.e., 3rdand 18thh in pigeons.
  5. Prediction of meteorological drought by using hybrid support vector regression optimized with HHO versus PSO algorithms
    Malik A, Tikhamarine Y, Sammen SS, Abba SI, Shahid S
    Environ Sci Pollut Res Int, 2021 Mar 22.
    PMID: 33751346 DOI: 10.1007/s11356-021-13445-0
    Drought is considered one of the costliest natural disasters that result in water scarcity and crop damage almost every year. Drought monitoring and forecasting are essential for the efficient management of water resources and sustainability in agriculture. However, the design of a consistent drought prediction model based on the dynamic relationship of the drought index with its antecedent values remains a challenging task. In the present research, the SVR (support vector regression) model was hybridized with two different optimization algorithms namely; Particle Swarm Optimization (PSO) and Harris Hawks Optimization (HHO) for reliable prediction of effective drought index (EDI) 1 month ahead, at different locations of Uttarakhand State of India. The inputs of the models were selected through partial autocorrelation function (PACF) analysis. The output produced by the SVR-HHO and SVR-PSO models was compared with the EDI estimated from observed data using five statistical indicators, i.e., RMSE (Root Mean Square Error), MAE (Mean Absolute Error), COC (Coefficient of Correlation), NSE (Nash-Sutcliffe Efficiency), WI (Willmott Index), and graphical inspection of radar-chart, time-variation plot, box-whisker plot, and Taylor diagram. Appraisal of results indicates that the SVR-HHO model (RMSE = 0.535-0.965, MAE = 0.363-0.622, NSE = 0.558-0.860, COC = 0.760-0.930, and WI = 0.862-0.959) outperformed the SVR-PSO model (RMSE = 0.546-0.967, MAE = 0.372-0.625, NSE = 0.556-0.855, COC = 0.758-0.929, and WI = 0.861-0.956) in predicting EDI. Visual inspection of model performances also showed a better performance of SVR-HHO compared to SVR-PSO in replicating the median, inter-quartile range, spread, and pattern of the EDI estimated from observed rainfall. The results indicate that the hybrid SVR-HHO approach can be utilized for reliable EDI predictions in the study area.
  6. Projection of temperature extremes of Egypt using CMIP6 GCMs under multiple shared socioeconomic pathways
    Hamed MM, Salehie O, Nashwan MS, Shahid S
    Environ Sci Pollut Res Int, 2023 Mar;30(13):38063-38075.
    PMID: 36576621 DOI: 10.1007/s11356-022-24985-4
    Global warming has amplified the frequency of temperature extremes, especially in hot dry countries, which could have serious consequences for the natural and built environments. Egypt is one of the hot desert climate regions that are more susceptible to climate change and associated hazards. This study attempted to project the changes in temperature extremes for three Shared Socioeconomic Pathways (SSPs), namely, SSP1-2.6, SSP2-4.5, and SSP5-8.5 and two future periods (early future: 2020-2059 and late future: 2060-2099) by using daily maximum (Tmax) and minimum temperature (Tmin) of general circulation model (GCMs) of Coupled Model Inter-comparison Project phase 6 (CMIP6). The findings showed that most temperature extreme indices would increase especially by the end of the century. In the late future, the change in the mean Tmin (4.3 °C) was projected to be higher than the mean Tmax (3.7 °C). Annual maximum Tmax, temperature above 95th percentile of Tmax, and the number of hot days above 40 °C and 45 °C were projected to increase in the range 3.0‒5.4 °C, 1.5‒4.8 °C, 20‒95 days, and 10‒52 days, respectively. In contrast, the annual minimum of Tmin, temperature below the 5th percentile, and the annual percentage of cold nights were projected to change in the range of 2.95‒5.0 °C, 1.4‒3.6 °C, and - 0.1‒0.1%, respectively. In all the cases, the lowest changes would be for SSP1-2.6 in the early period and the greatest changes for SSP5-8.5 in the late period. The study indicates that the country is likely to experience a rise in hot extremes and a decline in cold extremes. Therefore, Egypt should take long-term adaptation plans to build social resiliency to rising hot extremes.
  7. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration
    Song YH, Chung ES, Shahid S, Kim Y, Kim D
    Sci Data, 2023 Aug 26;10(1):568.
    PMID: 37633988 DOI: 10.1038/s41597-023-02475-7
    Reliable projection of evapotranspiration (ET) is important for planning sustainable water management for the agriculture field in the context of climate change. A global dataset of monthly climate variables was generated to estimate potential ET (PET) using 14 General Circulation Models (GCMs) for four main shared socioeconomic pathways (SSPs). The generated dataset has a spatial resolution of 0.5° × 0.5° and a period ranging from 1950 to 2100 and can estimate historical and future PET using the Penman-Monteith method. Furthermore, this dataset can be applied to various PET estimation methods based on climate variables. This paper presents that the dataset generated to estimate future PET could reflect the greenhouse gas concentration level of the SSP scenarios in latitude bands. Therefore, this dataset can provide vital information for users to select appropriate GCMs for estimating reasonable PETs and help determine bias correction methods to reduce between observation and model based on the scale of climate variables in each GCM.
  8. Sustaining the future: How green capabilities and digitalization drive sustainability in modern business
    Li Z, Rasool S, Cavus MF, Shahid W
    Heliyon, 2024 Jan 15;10(1):e24158.
    PMID: 38234898 DOI: 10.1016/j.heliyon.2024.e24158
    In recent years, the unprecedented growth in environmental vulnerabilities has made the firms realize the need for environmental protection. With this, the rapid surge for ecological preservation has made worldwide businesses divert their focus toward greener practices that ensure the firm's financial and environmental performance. This study examines the relationships between green management strategies (green dynamic capabilities, internal green supply chain management and green technology adoption), and organizational outcomes, specifically environmental and financial performance. The data was collected from the 471 employees working in the manufacturing firms. Utilizing the Structural Equation Modeling (SEM) method via Smart-PLS, our findings show the importance of integrating green practices in supply chain management, dynamic capabilities, and technology adoption to enhance both environmental and financial outcomes under the moderating role of industry dynamism and green knowledge acquisition.
  9. Fulltext UWB Antenna with Enhanced Directivity for Applications in Microwave Medical Imaging
    Awan D, Bashir S, Khan S, Al-Bawri SS, Dalarsson M
    Sensors (Basel), 2024 Feb 18;24(4).
    PMID: 38400473 DOI: 10.3390/s24041315
    Microwave medical imaging (MMI) is experiencing a surge in research interest, with antenna performance emerging as a key area for improvement. This work addresses this need by enhancing the directivity of a compact UWB antenna using a Yagi-Uda-inspired reflector antenna. The proposed reflector-loaded antenna (RLA) exhibited significant gain and directivity improvements compared to a non-directional reference antenna. When analyzed for MMI applications, the RLA showed a maximum increase of 4 dBi in the realized gain and of 14.26 dB in the transmitted field strength within a human breast model. Moreover, it preserved the shape of time-domain input signals with a high correlation factor of 94.86%. To further validate our approach, another non-directional antenna with proven head imaging capabilities was modified with a reflector, achieving similar directivity enhancements. The combined results demonstrate the feasibility of RLAs for improved performance in MMI systems.
  10. Exploring clinical specialists' perspectives on the future role of AI: evaluating replacement perceptions, benefits, and drawbacks
    Daniyal M, Qureshi M, Marzo RR, Aljuaid M, Shahid D
    BMC Health Serv Res, 2024 May 09;24(1):587.
    PMID: 38725039 DOI: 10.1186/s12913-024-10928-x
    BACKGROUND OF STUDY: Over the past few decades, the utilization of Artificial Intelligence (AI) has surged in popularity, and its application in the medical field is witnessing a global increase. Nevertheless, the implementation of AI-based healthcare solutions has been slow in developing nations like Pakistan. This unique study aims to assess the opinion of clinical specialists on the future replacement of AI, its associated benefits, and its drawbacks in form southern region of Pakistan.

    MATERIAL AND METHODS: A cross-sectional selective study was conducted from 140 clinical specialists (Surgery = 24, Pathology = 31, Radiology = 35, Gynecology = 35, Pediatric = 17) from the neglected southern Punjab region of Pakistan. The study was analyzed using χ2 - the test of association and the nexus between different factors was examined by multinomial logistic regression.

    RESULTS: Out of 140 respondents, 34 (24.3%) believed hospitals were ready for AI, while 81 (57.9%) disagreed. Additionally, 42(30.0%) were concerned about privacy violations, and 70(50%) feared AI could lead to unemployment. Specialists with less than 6 years of experience are more likely to embrace AI (p = 0.0327, OR = 3.184, 95% C.I; 0.262, 3.556) and those who firmly believe that AI knowledge will not replace their future tasks exhibit a lower likelihood of accepting AI (p = 0.015, OR = 0.235, 95% C.I: (0.073, 0.758). Clinical specialists who perceive AI as a technology that encompasses both drawbacks and benefits demonstrated a higher likelihood of accepting its adoption (p = 0.084, OR = 2.969, 95% C.I; 0.865, 5.187).

    CONCLUSION: Clinical specialists have embraced AI as the future of the medical field while acknowledging concerns about privacy and unemployment.

  11. Fulltext Latency-Sensitive Function Placement among Heterogeneous Nodes in Serverless Computing
    Shahid U, Ahmed G, Siddiqui S, Shuja J, Balogun AO
    Sensors (Basel), 2024 Jun 27;24(13).
    PMID: 39000973 DOI: 10.3390/s24134195
    Function as a Service (FaaS) is highly beneficial to smart city infrastructure due to its flexibility, efficiency, and adaptability, specifically for integration in the digital landscape. FaaS has serverless setup, which means that an organization no longer has to worry about specific infrastructure management tasks; the developers can focus on how to deploy and create code efficiently. Since FaaS aligns well with the IoT, it easily integrates with IoT devices, thereby making it possible to perform event-based actions and real-time computations. In our research, we offer an exclusive likelihood-based model of adaptive machine learning for identifying the right place of function. We employ the XGBoost regressor to estimate the execution time for each function and utilize the decision tree regressor to predict network latency. By encompassing factors like network delay, arrival computation, and emphasis on resources, the machine learning model eases the selection process of a placement. In replication, we use Docker containers, focusing on serverless node type, serverless node variety, function location, deadlines, and edge-cloud topology. Thus, the primary objectives are to address deadlines and enhance the use of any resource, and from this, we can see that effective utilization of resources leads to enhanced deadline compliance.
  12. Fulltext Changes in wet bulb globe temperature and risk to heat-related hazards in Bangladesh
    Kamal ASMM, Fahim AKF, Shahid S
    Sci Rep, 2024 May 06;14(1):10417.
    PMID: 38710893 DOI: 10.1038/s41598-024-61138-8
    The rise in temperatures and changes in other meteorological variables have exposed millions of people to health risks in Bangladesh, a densely populated, hot, and humid country. To better assess the threats climate change poses to human health, the wet bulb globe temperature (WBGT) is an important indicator of human heat stress. This study utilized high-resolution reanalysis data from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF ERA5) to analyze the spatiotemporal changes in outdoor WBGT across Bangladesh from 1979 to 2021, employing Liljegren's model. The study revealed an increase in the annual average WBGT by 0.08-0.5 °C per decade throughout the country, with a more pronounced rise in the southeast and northeast regions. Additionally, the number of days with WBGT levels associated with high and extreme risks of heat-related illnesses has shown an upward trend. Specifically, during the monsoon period (June to September), there has been an increase of 2-4 days per decade, and during the pre-monsoon period (March to May), an increase of 1-3 days per decade from 1979 to 2021. Furthermore, the results indicated that the escalation in WBGT has led to a five-fold increase in affected areas and a three-fold increase in days of high and extreme heat stress during the monsoon season in recent years compared to the earlier period. Trend and relative importance analyses of various meteorological variables demonstrated that air temperature is the primary driver behind Bangladesh's rising WBGT and related health risks, followed by specific humidity, wind speed, and solar radiation.
  13. A new insight for real-time wastewater quality prediction using hybridized kernel-based extreme learning machines with advanced optimization algorithms
    Alavi J, Ewees AA, Ansari S, Shahid S, Yaseen ZM
    Environ Sci Pollut Res Int, 2022 Mar;29(14):20496-20516.
    PMID: 34741267 DOI: 10.1007/s11356-021-17190-2
    Accurate prediction of inlet chemical oxygen demand (COD) is vital for better planning and management of wastewater treatment plants. The COD values at the inlet follow a complex nonstationary pattern, making its prediction challenging. This study compared the performance of several novel machine learning models developed through hybridizing kernel-based extreme learning machines (KELMs) with intelligent optimization algorithms for the reliable prediction of real-time COD values. The combined time-series learning method and consumer behaviours, estimated from water-use data (hour/day), were used as the supplementary inputs of the hybrid KELM models. Comparison of model performances for different input combinations revealed the best performance using up to 2-day lag values of COD with the other wastewater properties. The results also showed the best performance of the KELM-salp swarm algorithm (SSA) model among all the hybrid models with a minimum root mean square error of 0.058 and mean absolute error of 0.044.
  14. Fulltext Proximate composition, nutritional attributes and mineral composition of Peperomia pellucida L. (Ketumpangan Air) grown in Malaysia
    Ooi DJ, Iqbal S, Ismail M
    Molecules, 2012 Sep 17;17(9):11139-45.
    PMID: 22986924 DOI: 10.3390/molecules170911139
    This study presents the proximate and mineral composition of Peperomia pellucida L., an underexploited weed plant in Malaysia. Proximate analysis was performed using standard AOAC methods and mineral contents were determined using atomic absorption spectrometry. The results indicated Peperomia pellucida to be rich in crude protein, carbohydrate and total ash contents. The high amount of total ash (31.22%)suggests a high-value mineral composition comprising potassium, calcium and iron as the main elements. The present study inferred that Peperomia pellucida would serve as a good source of protein and energy as well as micronutrients in the form of a leafy vegetable for human consumption.
  15. Fulltext Comparing the morbidity of external laryngeal nerve injury in thyroid surgery with and without identifying the nerve using intraoperative neuromonitoring
    Khaled AO, Irfan M, Baharudin A, Shahid H
    Med J Malaysia, 2012 Jun;67(3):289-92.
    PMID: 23082419 MyJurnal
    To describe and determine the possibility of surgical trauma to the external branch of the superior laryngeal nerve and to assess the role of intraoperative neuromonitoring in thyroid surgery.
  16. Fulltext Harmonic scalpel for a bloodless partial glossectomy: a case report
    Irfan M, Aliyu YA, Baharudin A, Shahid H
    Med J Malaysia, 2011 Jun;66(2):148-9.
    PMID: 22106699
    Tongue surgery is almost always complicated by intraoperative bleeding. Its rich blood supply especially from the lingual vessels makes the operative field bloody. Electrocautery has been widely used to replace cold scissors in order to achieve better hemostasis. The use of ultrasonic harmonic scalpel for glossectomy is still new in this country. We report a case of partial glossectomy using the harmonic scalpel in a patient who had a squamous cell carcinoma of the lateral border of the tongue.
  17. Fulltext Intraparotid facial nerve schwannoma: a case report
    Irfan M, Shahid H, Yusri MM, Venkatesh RN
    Med J Malaysia, 2011 Jun;66(2):150-1.
    PMID: 22106700 MyJurnal
    Schwannoma in the head and neck region is very rare. The tumour occurring in the intraparotid facial nerve is even rarer. A patient presenting with a parotid swelling with facial nerve paralysis is not pathognomonic of a facial nerve schwannoma. However it may occur because enlargement of the parotid, by any kind of tumour especially a malignant one can cause facial nerve paralysis. We report a case of an intraparotid facial nerve schwannoma, in a patient who presented with parotid enlargement and facial nerve paralysis.
  18. Fulltext Ingestion of a voice-master prosthesis followed by a potentially fatal aspiration
    Philip R, Imran AG, Dinsuhaimi S, Shahid H
    Med J Malaysia, 2006 Jun;61(2):233-5.
    PMID: 16898319 MyJurnal
    Various complications are associated with the use of indwelling voice prostheses. We present problems faced by a patient with his Voice-Master prosthesis, the ingestion of the prosthesis followed by a potentially fatal aspiration. The Voice-Master is unique in that in can be re-inserted. The safety strap is removed after primary insertion once the prosthesis is secure. However, during re-insertions this safety mechanism is no longer present. Therefore we recommend the placement of a temporary stitch or tie to minimize the risks of ingestion or aspiration of the prosthesis during re-insertions.
  19. Hearing screening of infants in Neonatal Unit, Hospital Universiti Sains Malaysia using transient evoked otoacoustic emissions
    Khairi MD, Din S, Shahid H, Normastura AR
    J Laryngol Otol, 2005 Sep;119(9):678-83.
    PMID: 16156907
    The objective of this prospective study was to report on the prevalence of hearing impairment in the neonatal unit population. From 15 February 2000 to 15 March 2000 and from 15 February 2001 to 15 May 2001, 401 neonates were screened using transient evoked otoacoustic emissions (TEOAE) followed by second-stage screening of those infants who failed the initial test. Eight (2 per cent) infants failed one ear and 23 (5.74 per cent) infants failed both ears, adding up to 7.74 per cent planned for second-stage screening. Five out of 22 infants who came for the follow up failed the screening, resulting in a prevalence of hearing impairment of 1 per cent (95 per cent confidence interval [95% CI]: 0.0-2.0). Craniofacial malformations, very low birth weight, ototoxic medication, stigmata/syndromes associated with hearing loss and hyperbilirubinaemia at the level of exchange tranfusion were identified to be independent significant risk factors for hearing impairment, while poor Apgar scores and mechanical ventilation of more than five days were not. In conclusion, hearing screening in high-risk neonates revealed a total of 1 per cent with hearing loss. The changes in the risk profile indicate improved perinatal handling in a neonatal population at risk for hearing disorders.
  20. Modeling of wastewater quality in an urban area during festival and rainy days
    Obaid HA, Shahid S, Basim KN, Chelliapan S
    Water Sci Technol, 2015;72(6):1029-42.
    PMID: 26360765 DOI: 10.2166/wst.2015.297
    Water pollution during festival periods is a major problem in all festival cities across the world. Reliable prediction of water pollution is essential in festival cities for sewer and wastewater management in order to ensure public health and a clean environment. This article aims to model the biological oxygen demand (BOD(5)), and total suspended solids (TSS) parameters in wastewater in the sewer networks of Karbala city center during festival and rainy days using structural equation modeling and multiple linear regression analysis methods. For this purpose, 34 years (1980-2014) of rainfall, temperature and sewer flow data during festival periods in the study area were collected, processed, and employed. The results show that the TSS concentration increases by 26-46 mg/l while BOD(5) concentration rises by 9-19 mg/l for an increase of rainfall by 1 mm during festival periods. It was also found that BOD(5) concentration rises by 4-17 mg/l for each increase of 10,000 population.
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